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工程化用于芳香族氨基酸和神经化学物质的配体特异性生物传感器。

Engineering ligand-specific biosensors for aromatic amino acids and neurochemicals.

作者信息

Rottinghaus Austin G, Xi Chenggang, Amrofell Matthew B, Yi Hyojeong, Moon Tae Seok

机构信息

Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA.

Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA; Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, MO, USA.

出版信息

Cell Syst. 2022 Mar 16;13(3):204-214.e4. doi: 10.1016/j.cels.2021.10.006. Epub 2021 Nov 11.

Abstract

Microbial biosensors have diverse applications in metabolic engineering and medicine. Specific and accurate quantification of chemical concentrations allows for adaptive regulation of enzymatic pathways and temporally precise expression of diagnostic reporters. Although biosensors should differentiate structurally similar ligands with distinct biological functions, such specific sensors are rarely found in nature and challenging to create. Using E. coli Nissle 1917, a generally regarded as safe microbe, we characterized two biosensor systems that promiscuously recognize aromatic amino acids or neurochemicals. To improve the sensors' selectivity and sensitivity, we applied rational protein engineering by identifying and mutagenizing amino acid residues and successfully demonstrated the ligand-specific biosensors for phenylalanine, tyrosine, phenylethylamine, and tyramine. Additionally, our approach revealed insights into the uncharacterized structure of the FeaR regulator, including critical residues in ligand binding. These results lay the groundwork for developing kinetically adaptive microbes for diverse applications. A record of this paper's transparent peer review process is included in the supplemental information.

摘要

微生物生物传感器在代谢工程和医学领域有着广泛的应用。对化学物质浓度进行特异性和准确的定量,能够实现对酶促途径的适应性调节以及诊断报告基因的时间精确表达。尽管生物传感器应区分具有不同生物学功能的结构相似配体,但这类特异性传感器在自然界中很少见,且难以构建。我们利用普遍认为安全的微生物大肠杆菌Nissle 1917,对两种能混杂识别芳香族氨基酸或神经化学物质的生物传感器系统进行了表征。为提高传感器的选择性和灵敏度,我们通过鉴定和诱变氨基酸残基应用了合理的蛋白质工程,并成功展示了用于苯丙氨酸、酪氨酸、苯乙胺和酪胺的配体特异性生物传感器。此外,我们的方法揭示了对FeaR调节因子未表征结构的见解,包括配体结合中的关键残基。这些结果为开发适用于多种应用的动力学适应性微生物奠定了基础。本文透明的同行评审过程记录包含在补充信息中。

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